Variants identified in a GWAS meta-analysis for blood lipids are associated with the lipid response to fenofibrate

Pharmacogenomics of Cardiovascular Drugs for Atherothrombotic, Thromboembolic and Atherosclerotic Risk

PURPOSE OF REVIEW

Advances in pharmacogenomics have paved the way for personalized medicine. Cardiovascular diseases still represent the leading cause of mortality in the world. The aim of this review is to summarize the background, rationale, and evidence of pharmacogenomics in cardiovascular medicine, in particular, the use of antiplatelet drugs, anticoagulants, and drugs used for the treatment of dyslipidemia.

RECENT FINDINGS

Randomized clinical trials have supported the role of a genotype-guided approach for antiplatelet therapy in patients with coronary heart disease undergoing percutaneous coronary interventions. Numerous studies demonstrate how the risk of ineffectiveness of new oral anticoagulants and vitamin K anticoagulants is linked to various genetic polymorphisms. Furthermore, there is growing evidence to support the association of some genetic variants and poor adherence to statin therapy, for example, due to the appearance of muscular symptoms. There is evidence for resistance to some drugs for the treatment of dyslipidemia, such as anti-PCSK9.

SUMMARY

Pharmacogenomics has the potential to improve patient care by providing the right drug to the right patient and could guide the identification of new drug therapies for cardiovascular disease. This is very important in cardiovascular diseases, which have high morbidity and mortality. The improvement in therapy could be reflected in the reduction of healthcare costs and patient mortality.

Interaction between APOE, APOA1, and LPL Gene Polymorphisms and Variability in Changes in Lipid and Blood Pressure following Orange Juice Intake: A Pilot Study

SCOPE

Chronic orange juice intake is associated with reduced risk of cardiovascular disease, however, a large inter-individual variability in response to orange juice for lipid profile and blood pressure has been observed. This heterogeneity in responsiveness could be associated with single nucleotide polymorphism (SNP), which has not been previously addressed. This study aims to investigate the influence of SNP in apolipoprotein E (APOE), apolipoprotein A1 (APOA1), mevalonate (MVK), and lipase lipoprotein (LPL) genes in the biological response after chronic orange juice intake.

METHODS AND RESULTS

Forty-six volunteers ingested 500 mL daily for 60 days and blood pressure and biochemical parameters are measured. Also, SNPs in APOE, APOA1, MVK, and LPL genes are genotyped in the volunteers that are medium/high excretors of flavanone metabolites. Genotypes CC (APOA1), AA, and GG (LPL) are associated with positive health effects of orange juice and the CC (APOE), GG (APOA1), GG, and AA (LPL) genotypes are associated with no effects of orange juice consumption (p < 0.05).

CONCLUSION

These results identify for the first-time SNP associated with effects of orange juice on lipid levels and blood pressure, results that may provide bases for future precise nutritional recommendations regarding this flavanone-rich food to lower the risk for cardiovascular disease.

A Gene Variation at the ZPR1 Locus (rs964184) Interacts With the Type of Diet to Modulate Postprandial Triglycerides in Patients With Coronary Artery Disease: From the Coronary Diet Intervention With Olive Oil and Cardiovascular Prevention Study

Background and Aims

rs964184 variant in the ZPR1 gene has been associated with blood lipids levels both in fasting and postprandial state and with the risk of myocardial infarction in high-risk cardiovascular patients. However, whether this association is modulated by diet has not been studied.

Objective

To investigate whether the type of diet (low-fat or Mediterranean diets) interacts with genetic variability at this loci to modulate fasting and postprandial lipids in coronary patients.

Materials and Methods

The genotype of the rs964184 polymorphism was determined in the Cordioprev Study population (NCT00924937). Fasting and Postprandial triglycerides were assessed before and after 3 years of dietary intervention with either a Mediterranean or a low-fat diet. Postprandial lipid assessment was done by a 4-h oral fat tolerance test (OFTT). Differences in triglycerides levels were identified using repeated-measures ANCOVA.

Results

From 523 patients (85% males, mean age 59 years) that completed the OFTT at baseline and after 3 years of intervention and had complete genotype information, 125 of them were carriers of the risk allele G. At the start of the study, these patients showed a higher fasting and postprandial triglycerides (TG) plasma levels. After 3 years of dietary intervention, G-carriers following a Mediterranean Diet maintained higher fasting and postprandial triglycerides, while those on the low-fat diet reduced their postprandial triglycerides to similar values to the population without the G-allele.

Conclusion

After 3 years of dietary intervention, the altered postprandial triglyceride response induced by genetic variability in the rs964184 polymorphism of the ZPR1 gene can be modulated by a low-fat diet, better than by a Mediterranean diet, in patients with coronary artery disease.

Fibrate pharmacogenomics: expanding past the genome

Fibrates are a medication class prescribed for decades as 'broad-spectrum' lipid-modifying agents used to lower blood triglyceride levels and raise high-density lipoprotein cholesterol levels. Such lipid changes are associated with a decrease in cardiovascular disease, and fibrates are commonly used to reduce risk of dangerous cardiovascular outcomes. As with most drugs, it is well established that response to fibrate treatment is variable, and this variation is heritable. This has motivated the investigation of pharmacogenomic determinants of response, and multiple studies have discovered a number of genes associated with fibrate response. Similar to other complex traits, the interrogation of single nucleotide polymorphisms using candidate gene or genome-wide approaches has not revealed a substantial portion of response variation. However, recent innovations in technological platforms and advances in statistical methodologies are revolutionizing the use and integration of other 'omes' in pharmacogenomics studies. Here, we detail successes, challenges, and recent advances in fibrate pharmacogenomics.

Gene-environment interactions due to quantile-specific heritability of triglyceride and VLDL concentrations

"Quantile-dependent expressivity" is a dependence of genetic effects on whether the phenotype (e.g., triglycerides) is high or low relative to its distribution in the population. Quantile-specific offspring-parent regression slopes (β_OP) were estimated by quantile regression for 6227 offspring-parent pairs. Quantile-specific heritability (h²), estimated by 2β_OP/(1 + r_spouse), decreased 0.0047 ± 0.0007 (P = 2.9 × 10^-14) for each one-percent decrement in fasting triglyceride concentrations, i.e., h² ± SE were: 0.428 ± 0.059, 0.230 ± 0.030, 0.111 ± 0.015, 0.050 ± 0.016, and 0.033 ± 0.010 at the 90th, 75th, 50th, 25th, and 10th percentiles of the triglyceride distribution, respectively. Consistent with quantile-dependent expressivity, 11 drug studies report smaller genotype differences at lower (post-treatment) than higher (pre-treatment) triglyceride concentrations. This meant genotype-specific triglyceride changes could not move in parallel when triglycerides were decreased pharmacologically, so that subtracting pre-treatment from post-treatment triglyceride levels necessarily created a greater triglyceride decrease for the genotype with a higher pre-treatment value (purported precision-medicine genetic markers). In addition, sixty-five purported gene-environment interactions were found to be potentially attributable to triglyceride's quantile-dependent expressivity, including gene-adiposity (APOA5, APOB, APOE, GCKR, IRS-1, LPL, MTHFR, PCSK9, PNPLA3, PPARγ2), gene-exercise (APOA1, APOA2, LPL), gene-diet (APOA5, APOE, INSIG2, LPL, MYB, NXPH1, PER2, TNFA), gene-alcohol (ALDH2, APOA5, APOC3, CETP, LPL), gene-smoking (APOC3, CYBA, LPL, USF1), gene-pregnancy (LPL), and gene-insulin resistance interactions (APOE, LPL).

Apolipoprotein C1: Its Pleiotropic Effects in Lipid Metabolism and Beyond

Apolipoprotein C1 (apoC1), the smallest of all apolipoproteins, participates in lipid transport and metabolism. In humans, APOC1 gene is in linkage disequilibrium with APOE gene on chromosome 19, a proximity that spurred its investigation. Apolipoprotein C1 associates with triglyceride-rich lipoproteins and HDL and exchanges between lipoprotein classes. These interactions occur via amphipathic helix motifs, as demonstrated by biophysical studies on the wild-type polypeptide and representative mutants. Apolipoprotein C1 acts on lipoprotein receptors by inhibiting binding mediated by apolipoprotein E, and modulating the activities of several enzymes. Thus, apoC1 downregulates lipoprotein lipase, hepatic lipase, phospholipase A2, cholesterylester transfer protein, and activates lecithin-cholesterol acyl transferase. By controlling the plasma levels of lipids, apoC1 relates directly to cardiovascular physiology, but its activity extends beyond, to inflammation and immunity, sepsis, diabetes, cancer, viral infectivity, and-not last-to cognition. Such correlations were established based on studies using transgenic mice, associated in the recent years with GWAS, transcriptomic and proteomic analyses. The presence of a duplicate gene, pseudogene APOC1P, stimulated evolutionary studies and more recently, the regulatory properties of the corresponding non-coding RNA are steadily emerging. Nonetheless, this prototypical apolipoprotein is still underexplored and deserves further research for understanding its physiology and exploiting its therapeutic potential.

Genetic Variants Associated With Plasma Lipids Are Associated With the Lipid Response to Niacin

Background Niacin is a broad-spectrum lipid-modulating drug, but its mechanism of action is unclear. Genome-wide association studies have identified multiple loci associated with blood lipid levels and lipoprotein (a). It is unknown whether these loci modulate response to niacin. Methods and Results Using data from the AIM - HIGH (Atherothrombosis Intervention in Metabolic Syndrome with Low HDL /High Triglycerides and Impact on Global Health Outcomes) trial (n=2054 genotyped participants), we determined whether genetic variations at validated loci were associated with a differential change in plasma lipids and lipoprotein (a) 1 year after randomization to either statin+placebo or statin+niacin in a variant-treatment interaction model. Nominally significant interactions ( P<0.05) were found for genetic variants in MVK , LIPC , PABPC 4, AMPD 3 with change in high-density lipoprotein cholesterol; SPTLC 3 with change in low-density lipoprotein cholesterol; TOM 1 with change in total cholesterol; PDXDC 1 and CYP 26A1 with change in triglycerides; and none for lipoprotein (a). We also investigated whether these loci were associated with cardiovascular events. The risk of coronary disease related death was higher in the minor allele carriers at the LIPC locus in the placebo group (odds ratio 2.08, 95% confidence interval 1.11-3.90, P=0.02) but not observed in the niacin group (odds ratio 0.89, 95% confidence interval 0.48-1.65, P=0.7); P-interaction =0.02. There was a greater risk for acute coronary syndrome (odds ratio 1.85, 95% confidence interval 1.16-2.77, P=0.02) and revascularization events (odds ratio 1.64, 95% confidence interval 1.2-2.22, P=0.002) in major allele carriers at the CYP 26A1 locus in the placebo group not seen in the niacin group. Conclusions Genetic variation at loci previously associated with steady-state lipid levels displays evidence for lipid response to niacin treatment. Clinical Trials Registration URL: https://www.clinicaltrials.gov . Unique identifier: NCT00120289.

Fast and Accurate Shared Segment Detection and Relatedness Estimation in Un-phased Genetic Data via TRUFFLE

Relationship estimation and segment detection between individuals is an important aspect of disease gene mapping. Existing methods are either tailored for computational efficiency or require phasing to improve accuracy. We developed TRUFFLE, a method that integrates computational techniques and statistical principles for the identification and visualization of identity-by-descent (IBD) segments using un-phased data. By skipping the haplotype phasing step and, instead, relying on a simpler region-based approach, our method is computationally efficient while maintaining inferential accuracy. In addition, an error model corrects for segment break-ups that occur as a consequence of genotyping errors. TRUFFLE can estimate relatedness for 3.1 million pairs from the 1000 Genomes Project data in a few minutes on a typical laptop computer. Consistent with expectation, we identified only three second cousin or closer pairs across different populations, while commonly used methods identified a large number of such pairs. Similarly, within populations, we identified many fewer related pairs. Compared to methods relying on phased data, TRUFFLE has comparable accuracy but is drastically faster and has fewer broken segments. We also identified specific local genomic regions that are commonly shared within populations, suggesting selection. When applied to pedigree data, we observed 99.6% accuracy in detecting 1^st to 5^th degree relationships. As genomic datasets become much larger, TRUFFLE can enable disease gene mapping through implicit shared haplotypes by accurate IBD segment detection.

Impact of gender and age on the association of the BUD13-ZNF259 rs964184 polymorphism with coronary heart disease

OBJECTIVE

Coronary heart disease (CHD) is the most common cause of death worldwide. This study aimed to validate the association of the rs964184 polymorphism with the CHD risk and included 874 CHD patients and 776 controls.

METHODS

rs964184 polymorphism genotyping was performed using Tm-shift polymerase chain reaction.

RESULTS

A strong association of the rs964184 polymorphism with CHD was found (genotype: X²=14.365, p=0.001; allele: X²=14.191, p=1.67x10^-4; power=0.965). Gender analysis revealed a significant association only in males (genotype: X²=12.387, p=0.002; allele: X²=12.404, p=4.32x10^-4; OR=1.467, 95% CI=1.185-1.817, power=0.945). Age and gender analyses revealed significant associations of the rs964184 polymorphism with CHD in males between the ages of 55 and 65 years (genotype: X²=10.070, p=0.007; allele: X²=10.077, p=0.002; OR=1.706, 95% CI=1.224-2.377, power=0.996) and in females older than 65 years (genotype: X²=9.462, p=0.009; allele: X²=9.560, p=0.002; OR=2.112, 95% CI=1.308-3.412, power=0.994). Further subgroup analysis suggested that rs964184 genotypes were significantly associated with TG levels in the patients (r=0.191, adjusted p=1.05x10^-5) and controls (r=0.101, adjusted p=0.026).

CONCLUSION

Our results indicate that both gender and age have great impacts on the association of the rs964184 polymorphism with CHD among Chinese.

Reverse GWAS: Using genetics to identify and model phenotypic subtypes

Recent and classical work has revealed biologically and medically significant subtypes in complex diseases and traits. However, relevant subtypes are often unknown, unmeasured, or actively debated, making automated statistical approaches to subtype definition valuable. We propose reverse GWAS (RGWAS) to identify and validate subtypes using genetics and multiple traits: while GWAS seeks the genetic basis of a given trait, RGWAS seeks to define trait subtypes with distinct genetic bases. Unlike existing approaches relying on off-the-shelf clustering methods, RGWAS uses a novel decomposition, MFMR, to model covariates, binary traits, and population structure. We use extensive simulations to show that modelling these features can be crucial for power and calibration. We validate RGWAS in practice by recovering a recently discovered stress subtype in major depression. We then show the utility of RGWAS by identifying three novel subtypes of metabolic traits. We biologically validate these metabolic subtypes with SNP-level tests and a novel polygenic test: the former recover known metabolic GxE SNPs; the latter suggests subtypes may explain substantial missing heritability. Crucially, statins, which are widely prescribed and theorized to increase diabetes risk, have opposing effects on blood glucose across metabolic subtypes, suggesting the subtypes have potential translational value.

An Exome-Wide Sequencing Study of the GOLDN Cohort Reveals Novel Associations of Coding Variants and Fasting Plasma Lipids

Background: Associations of both common and rare genetic variants with fasting blood lipids have been extensively studied. However, most of the rare coding variants associated with lipids are population-specific, and exploration of genetic data from diverse population samples may enhance the identification of novel associations with rare variants. Results: We searched for novel coding genetic variants associated with fasting lipid levels in 894 samples from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) with exome-wide sequencing-based genotype data. In single variant tests, one variant (rs11171663 in ITGA7) was associated with fasting triglyceride levels (P = 7.66E-08), explaining approximately 3.2% of the total trait variance. In gene-based tests, we found statistically significant associations between ITGA7 (P = 1.77E-07) and SLCO2A1 (P = 7.18E-07) and triglycerides, as well as between POT1 (P = 3.00E-07) and low-density lipoprotein cholesterol. In another independent replication cohort consisting of 3,183 African American samples from Hypertension Genetic Epidemiology Network (HyperGEN) and the Genetic Epidemiology Network of Arteriopathy (GENOA), the top genes achieved P-values of 0.04 (ITGA7), 0.08 (SLCO2A1), and 0.02 (POT1). In GOLDN, gene transcript levels of ITGA7 and SLCO2A1 were associated with fasting triglycerides (P = 0.07 and P = 0.02), highlighting functional relevance of our findings. Conclusion: In this study, we present preliminary evidence of novel rare variant determinants of fasting lipids, and reveal potential underlying molecular mechanisms. Moreover, these results were replicated in an independent cohort. Our findings may inform novel biomarkers of disease risk and treatment targets.

Assessment of fenofibrate-methylation interactions on triglycerides using longitudinal family data

Background

Triglyceride (TG) concentrations decrease in response to fenofibrate treatment, and also are associated with DNA methylation. But how interactions between fenofibrate response and DNA methylation affect TGs remains unclear.

Methods

In the present study, we identified and compared differential methylation sites associated with TG concentrations in individuals before and after fenofibrate treatment. We then estimated interactions between fenofibrate treatment and methylation to identify differential methylation effects associated with fenofibrate treatment on TG concentrations using the entire longitudinal family sample. To account for within-family and within-individual corrections, the generalized estimating equations approach was used to estimate main and interaction effects between methylation sites and fenofibrate treatment, adjusting for potential confounders. Analyses were also performed with and without adjusting for high-density lipoprotein (HDL) concentrations.

Results

Prior to fenofibrate treatment, 23 cytosine-phosphate-guanine (CpG) sites were significantly associated with TG concentrations, while only 13 CpG sites were identified posttreatment, adjusting for HDL. Without adjusting for HDL, pretreatment, 20 CpG sites were significantly associated with TG concentrations, while only 12 CpG sites were identified posttreatment. Among these sites, only one differential site (cg19003390 in the CPT1A gene) overlapped from pre- and posttreatment measurements regardless of HDL adjustment. Furthermore, 11 methylation sites showed substantial interaction effects (p < 1.43 × 10⁻⁷with Bonferroni correction) with or without HDL adjustment when using the whole longitudinal data.

Conclusions

Our analyses suggest that DNA methylation likely modified the effect of fenofibrate on TG concentrations. Differential fenofibrate-associated methylation sites on TGs differed with and without adjusting for HDL concentrations, suggesting that these HDLs and TGs might share some common epigenetic processes.

The challenge of detecting genotype-by-methylation interaction: GAW20

BACKGROUND

GAW20 working group 5 brought together researchers who contributed 7 papers with the aim of evaluating methods to detect genetic by epigenetic interactions. GAW20 distributed real data from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study, including single-nucleotide polymorphism (SNP) markers, methylation (cytosine-phosphate-guanine [CpG]) markers, and phenotype information on up to 995 individuals. In addition, a simulated data set based on the real data was provided.

RESULTS

The 7 contributed papers analyzed these data sets with a number of different statistical methods, including generalized linear mixed models, mediation analysis, machine learning, W-test, and sparsity-inducing regularized regression. These methods generally appeared to perform well. Several papers confirmed a number of causative SNPs in either the large number of simulation sets or the real data on chromosome 11. Findings were also reported for different SNPs, CpG sites, and SNP-CpG site interaction pairs.

CONCLUSIONS

In the simulation (200 replications), power appeared generally good for large interaction effects, but smaller effects will require larger studies or consortium collaboration for realizing a sufficient power.

An adaptive gene-level association test for pedigree data

Background

We propose a gene-level association test that accounts for individual relatedness and population structures in pedigree data in the framework of linear mixed models (LMMs). Our method data-adaptively combines the results across a class of score-based tests, only requiring fitting a single null model (under the null hypothesis) for the whole genome, thereby being computationally efficient.

Results

We applied our approach to test for association with the high-density lipoprotein (HDL) ratio of post- and pretreatments in GAW20 data. Using the LMM similar to that used by Aslibekyan et al. (PLos One, 7:48663, 2012), our method identified 2 nearly significant genes (APOA5 and ZNF259) near rs964184, whereas neither the other gene-level tests nor the standard test on each individual single-nucleotide polymorphism (SNP) detected any significant gene in a genome-wide scan.

Conclusions

Gene-level association testing can be a complementary approach to the SNP-level association testing and our method is adaptive and efficient compared to several other existing gene-level association tests.

Methods and results from the genome-wide association group at GAW20

BACKGROUND

This paper summarizes the contributions from the Genome-wide Association Study group (GWAS group) of the GAW20. The GWAS group contributions focused on topics such as association tests, phenotype imputation, and application of empirical kinships. The goals of the GWAS group contributions were varied. A real or a simulated data set based on the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study was employed by different methods. Different outcomes and covariates were considered, and quality control procedures varied throughout the contributions.

RESULTS

The consideration of heritability and family structure played a major role in some contributions. The inclusion of family information and adaptive weights based on data were found to improve power in genome-wide association studies. It was proven that gene-level approaches are more powerful than single-marker analysis. Other contributions focused on the comparison between pedigree-based kinship and empirical kinship matrices, and investigated similar results in heritability estimation, association mapping, and genomic prediction. A new approach for linkage mapping of triglyceride levels was able to identify a novel linkage signal.

CONCLUSIONS

This summary paper reports on promising statistical approaches and findings of the members of the GWAS group applied on real and simulated data which encompass the current topics of epigenetic and pharmacogenomics.

Investigating potential causal relationships between SNPs, DNA methylation and HDL

Using data on 680 patients from the GAW20 real data set, we conducted Mendelian randomization (MR) studies to explore the causal relationships between methylation levels at selected probes (cytosine-phosphate-guanine sites [CpGs]) and high-density lipoprotein (HDL) changes (ΔHDL) using single-nucleotide polymorphisms (SNPs) as instrumental variables. Several methods were used to estimate the causal effects at CpGs of interest on ΔHDL, including a newly developed method that we call constrained instrumental variables (CIV). CIV performs automatic SNP selection while providing estimates of causal effects adjusted for possible pleiotropy, when the potentially-pleiotropic phenotypes are measured. For CpGs in or near the 10 genes identified as associated with ΔHDL using a family-based VC-score test, we compared CIV to Egger regression and the two-stage least squares (TSLS) method. All 3 approaches selected at least 1CpG in 2 genes-RNMT;C18orf19 and C6orf141-as showing a causal relationship with ΔHDL.

CpG-set association assessment of lipid concentration changes and DNA methylation

Epigenome association studies that test a large number of methylation sites suffer from stringent multiple-testing corrections. This study's goals were to investigate region-based associations between DNA methylation sites and lipid-level changes in response to the treatment with fenofibrate in the GAW20 data and to investigate whether improvements in power could be obtained by taking into account correlations between DNA methylation at neighboring cytosine-phosphate-guanine (CpG) sites. To this end, we applied both a recently developed block-based data-dimension-reduction approach and a region-based variance-component (VC) linear mixed model to GAW20 data. We compared analyses of unrelated individuals with familial data. The region-based VC approach using unrelated (independent) individuals identified the gene LGALS9C as significantly associated with changes in triglycerides. However, univariate tests of individual CpG sites yielded no valid statistically significant results.

Transmission-based association mapping of triglyceride levels in a longitudinal framework using quasi-likelihood

Complex genetic traits are often characterized by multiple quantitative phenotypes. Because values of such phenotypes vary over time, it is thought that analyses of longitudinal data on the phenotypes may lead to increased power in detecting genetic association. In this paper, we extend a transmission-based association test applying quasi-likelihood that has been developed by us to the longitudinal framework and to carry out a genome-wide association analysis of triglyceride levels based on the data provided in GAW20. We consider different phenotype definitions based on administration of fenofibrate and obtain significant association findings within genes involved in heart diseases.

An exome-wide sequencing study of lipid response to high-fat meal and fenofibrate in Caucasians from the GOLDN cohort

Our understanding of genetic influences on the response of lipids to specific interventions is limited. In this study, we sought to elucidate effects of rare genetic variants on lipid response to a high-fat meal challenge and fenofibrate (FFB) therapy in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) cohort using an exome-wide sequencing-based association study. Our results showed that the rare coding variants in ITGA7, SIPA1L2, and CEP72 are significantly associated with fasting LDL cholesterol response to FFB (P = 1.24E-07), triglyceride postprandial area under the increase (AUI) (P = 2.31E-06), and triglyceride postprandial AUI response to FFB (P = 1.88E-06), respectively. We sought to replicate the association for SIPA1L2 in the Heredity and Phenotype Intervention (HAPI) Heart Study, which included a high-fat meal challenge but not FFB treatment. The associated rare variants in GOLDN were not observed in the HAPI Heart study, and thus the gene-based result was not replicated. For functional validation, we found that gene transcript level of SIPA1L2 is associated with triglyceride postprandial AUI (P < 0.05) in GOLDN. Our study suggests unique genetic mechanisms contributing to the lipid response to the high-fat meal challenge and FFB therapy.

Genetic Variants in HSD17B3, SMAD3, and IPO11 Impact Circulating Lipids in Response to Fenofibrate in Individuals With Type 2 Diabetes

Individuals with type 2 diabetes (T2D) and dyslipidemia are at an increased risk of cardiovascular disease. Fibrates are a class of drugs prescribed to treat dyslipidemia, but variation in response has been observed. To evaluate common and rare genetic variants that impact lipid responses to fenofibrate in statin-treated patients with T2D, we examined lipid changes in response to fenofibrate therapy using a genomewide association study (GWAS). Associations were followed-up using gene expression studies in mice. Common variants in SMAD3 and IPO11 were marginally associated with lipid changes in black subjects (P < 5 × 10-6 ). Rare variant and gene expression changes were assessed using a false discovery rate approach. AKR7A3 and HSD17B13 were associated with lipid changes in white subjects (q < 0.2). Mice fed fenofibrate displayed reductions in Hsd17b13 gene expression (q < 0.1). Associations of variants in SMAD3, IPO11, and HSD17B13, with gene expression changes in mice indicate that transforming growth factor-beta (TGF-β) and NRF2 signaling pathways may influence fenofibrate effects on dyslipidemia in patients with T2D.

Pharmacogenetics of Lipid-Lowering Agents: Precision or Indecision Medicine?

Lipid-lowering medications, particularly statins, have been a popular target for pharmacogenetic studies. A handful of genes have shown promise for predicting response to therapy from the perspective of lipid lowering, as well as myopathy. A number of genes have been implicated and have biological plausibility based on their involvement with the pharmacokinetics or pharmacodynamics of statins or other lipid-lowering medications. The level of confidence and replication of these findings varies, although several associations are likely true. Novel classes of lipid-lowering therapy have opened up new possibilities in the treatment of severe inherited forms of dyslipidemia, making the identification of such mutations an important pharmacogenetic predictor of failure of standard therapy, with potential response to novel therapy. Advances in next-generation sequencing technology bring the application of pharmacogenetics even closer to routine clinical practice.

A genome-wide study of lipid response to fenofibrate in Caucasians: a combined analysis of the GOLDN and ACCORD studies

BACKGROUND

Fibrates are commonly prescribed for hypertriglyceridemia, but they also lower LDL cholesterol and increase HDL cholesterol. Large interindividual variations in lipid response suggest that some patients may benefit more than others and genetic studies could help identify such patients.

METHODS

We carried out the first genome-wide association study of lipid response to fenofibrate using data from two well-characterized clinical trials: the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) Study and the Action to Control Cardiovascular Risk in Diabetes (ACCORD) Study. Genome-wide association study data from both studies were imputed to the 1000 Genomes CEU reference panel (phase 1). Lipid response was modeled as the log ratio of the post-treatment lipid level to the pretreatment level. Linear mixed models (GOLDN, N=813 from 173 families) and linear regression models (ACCORD, N=781) adjusted for pretreatment lipid level, demographic variables, clinical covariates, and ancestry were used to evaluate the association of genetic markers with lipid response. Among Caucasians, the results were combined using inverse-variance weighted fixed-effects meta-analyses. The main findings from the meta-analyses were examined in other ethnic groups from the HyperTG study (N=267 Hispanics) and ACCORD (N=83 Hispanics, 138 African Americans).

RESULTS

A known lipid locus harboring the pre-B-cell leukemia homeobox 4 (PBX4) gene on chromosome 19 is important for LDL cholesterol response to fenofibrate (smallest P=1.5×10). The main results replicated with nominal statistical significance in Hispanics from ACCORD (P<0.05).

CONCLUSION

Future research should evaluate the usefulness of this locus to refine clinical strategies for lipid-lowering treatments.

Genome-wide association study of triglyceride response to a high-fat meal among participants of the NHLBI Genetics of Lipid Lowering Drugs and Diet Network (GOLDN)

OBJECTIVE

The triglyceride (TG) response to a high-fat meal (postprandial lipemia, PPL) affects cardiovascular disease risk and is influenced by genes and environment. Genes involved in lipid metabolism have dominated genetic studies of PPL TG response. We sought to elucidate common genetic variants through a genome-wide association (GWA) study in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN).

METHODS

The GOLDN GWAS discovery sample consisted of 872 participants within families of European ancestry. Genotypes for 2,543,887 variants were measured or imputed from HapMap. Replication of our top results was performed in the Heredity and Phenotype Intervention (HAPI) Heart Study (n = 843). PPL TG response phenotypes were constructed from plasma TG measured at baseline (fasting, 0 hour), 3.5 and 6 hours after a high-fat meal, using a random coefficient regression model. Association analyses were adjusted for covariates and principal components, as necessary, in a linear mixed model using the kinship matrix; additional models further adjusted for fasting TG were also performed. Meta-analysis of the discovery and replication studies (n = 1715) was performed on the top SNPs from GOLDN.

RESULTS

GOLDN revealed 111 suggestive (p < 1E-05) associations, with two SNPs meeting GWA significance level (p < 5E-08). Of the two significant SNPs, rs964184 demonstrated evidence of replication (p = 1.20E-03) in the HAPI Heart Study and in a joint analysis, was GWA significant (p = 1.26E-09). Rs964184 has been associated with fasting lipids (TG and HDL) and is near ZPR1 (formerly ZNF259), close to the APOA1/C3/A4/A5 cluster. This association was attenuated upon additional adjustment for fasting TG.

CONCLUSION

This is the first report of a genome-wide significant association with replication for a novel phenotype, namely PPL TG response. Future investigation into response phenotypes is warranted using pathway analyses, or newer genetic technologies such as metabolomics.

Functional variants of lipid level modifier MLXIPL, GCKR, GALNT2, CILP2, ANGPTL3 and TRIB1 genes in healthy Roma and Hungarian populations

The role of triglyceride metabolism in different diseases, such as cardiovascular or cerebrovascular diseases is still under extensive investigations. In genome-wide studies several polymorphisms have been reported, which are highly associated with plasma lipid level changes. Our goal was to examine eight variants: rs12130333 at the ANGPTL3, rs16996148 at the CILP2, rs17321515 at the TRIB1, rs17145738 and rs3812316 of the MLXIPL, rs4846914 at GALNT2, rs1260326 and rs780094 residing at the GCKR loci. A total of 399 Roma (Gypsy) and 404 Hungarian population samples were genotyped using PCR-RFLP method. Significant differences were found between Roma and Hungarian population samples in both MLXIPL variants (C allele frequency of rs17145738: 94.1% vs. 85.6%, C allele frequency of rs3812316: 94.2% vs. 86.8% in Romas vs. in Hungarians, p < 0.05), in ANGPTL3 (T allele frequency of rs1213033: 12.2% vs. 18.5% in Romas vs. Hungarians, p < 0.05) and GALNT2 (G allele frequency of rs4846914: 46.6% vs. 54.5% Romas vs. in Hungarians, p < 0.05), while no differences over SNPs could be verified and the known minor alleles showed no correlation with triglyceride levels in any population samples. The current study revealed fundamental differences of known triglyceride modifying SNPs in Roma population. Failure of finding evidence for affected triglyceride metabolism shows that these susceptibility genes are much less effective compared for example to the apolipoprotein A5 gene.

Nutrigenetics of cholesterol metabolism: observational and dietary intervention studies in the postgenomic era

Cholesterol metabolism is a well-defined responder to dietary intakes and a classic biomarker of cardiovascular health. For this reason, circulating cholesterol levels have become key in shaping nutritional recommendations by health authorities worldwide for better management of cardiovascular disease, a leading cause of mortality and one of the most costly health problems globally. Data from observational and dietary intervention studies, however, highlight a marked between-individual variability in the response of cholesterol metabolism to similar dietary protocols, a phenomenon linked to genetic heterogeneity. This review summarizes the postgenomic evidence of polymorphisms within cholesterol-associated genes relative to fasting circulating cholesterol levels under diverse nutritional conditions. A number of cholesterol-related gene-diet interactions are confirmed, which may have clinical importance, supporting a deeper look into the rapidly emerging field of nutrigenetics for meaningful conclusions that may eventually lead to genetically targeted dietary recommendations in the era of personalized nutrition.

The mammalian molybdenum enzymes of mARC

The "mitochondrial amidoxime reducing component" (mARC) is the most recently discovered molybdenum-containing enzyme in mammals. All mammalian genomes studied to date contain two mARC genes: MARC1 and MARC2. The proteins encoded by these genes are mARC-1 and mARC-2 and represent the simplest form of eukaryotic molybdenum enzymes, only binding the molybdenum cofactor. In the presence of NADH, mARC proteins exert N-reductive activity together with the two electron transport proteins cytochrome b5 type B and NADH cytochrome b5 reductase. This enzyme system is capable of reducing a great variety of N-hydroxylated substrates. It plays a decisive role in the activation of prodrugs containing an amidoxime structure, and in detoxification pathways, e.g., of N-hydroxylated purine and pyrimidine bases. It belongs to a group of drug metabolism enzymes, in particular as a counterpart of P450 formed N-oxygenated metabolites. Its physiological relevance, on the other hand, is largely unknown. The aim of this article is to summarize our current knowledge of these proteins with a special focus on the mammalian enzymes and their N-reductive activity.

Genetic risk scores associated with baseline lipoprotein subfraction concentrations do not associate with their responses to fenofibrate

Lipoprotein subclass concentrations are modifiable markers of cardiovascular disease risk. Fenofibrate is known to show beneficial effects on lipoprotein subclasses, but little is known about the role of genetics in mediating the responses of lipoprotein subclasses to fenofibrate. A recent genomewide association study (GWAS) associated several single nucleotide polymorphisms (SNPs) with lipoprotein measures, and validated these associations in two independent populations. We used this information to construct genetic risk scores (GRSs) for fasting lipoprotein measures at baseline (pre-fenofibrate), and aimed to examine whether these GRSs also associated with the responses of lipoproteins to fenofibrate. Fourteen lipoprotein subclass measures were assayed in 817 men and women before and after a three week fenofibrate trial. We set significance at a Bonferroni corrected alpha <0.05 (p < 0.004). Twelve subclass measures changed with fenofibrate administration (each p = 0.003 to <0.0001). Mixed linear models which controlled for age, sex, body mass index (BMI), smoking status, pedigree and study-center, revealed that GRSs were associated with eight baseline lipoprotein measures (p < 0.004), however no GRS was associated with fenofibrate response. These results suggest that the mechanisms for changes in lipoprotein subclass concentrations with fenofibrate treatment are not mediated by the genetic risk for fasting levels.

The N-reductive system composed of mitochondrial amidoxime reducing component (mARC), cytochrome b5 (CYB5B) and cytochrome b5 reductase (CYB5R) is regulated by fasting and high fat diet in mice

The mitochondrial amidoxime reducing component mARC is the fourth mammalian molybdenum enzyme. The protein is capable of reducing N-oxygenated structures, but requires cytochrome b5 and cytochrome b5 reductase for electron transfer to catalyze such reactions. It is well accepted that the enzyme is involved in N-reductive drug metabolism such as the activation of amidoxime prodrugs. However, the endogenous function of the protein is not fully understood. Among other functions, an involvement in lipogenesis is discussed. To study the potential involvement of the protein in energy metabolism, we tested whether the mARC protein and its partners are regulated due to fasting and high fat diet in mice. We used qRT-PCR for expression studies, Western Blot analysis to study protein levels and an N-reductive biotransformation assay to gain activity data. Indeed all proteins of the N-reductive system are regulated by fasting and its activity decreases. To study the potential impact of these changes on prodrug activation in vivo, another mice experiment was conducted. Model compound benzamidoxime was injected to mice that underwent fasting and the resulting metabolite of the N-reductive reaction, benzamidine, was determined. Albeit altered in vitro activity, no changes in the metabolite concentration in vivo were detectable and we can dispel concerns that fasting alters prodrug activation in animal models. With respect to high fat diet, changes in the mARC proteins occur that result in increased N-reductive activity. With this study we provide further evidence that the endogenous function of the mARC protein is linked with lipid metabolism.

ABCD2 alters peroxisome proliferator-activated receptor α signaling in vitro, but does not impair responses to fenofibrate therapy in a mouse model of diet-induced obesity

Fenofibrate is a peroxisome proliferator-activated receptor (PPAR) α ligand that has been widely used as a lipid-lowering agent in the treatment of hypertriglyceridemia. ABCD2 (D2) is a peroxisomal long-chain acyl-CoA transporter that is highly induced by fenofibrate in the livers of mice. To determine whether D2 is a modifier of fibrate responses, wild-type and D2-deficient mice were treated with fenofibrate for 14 days. The absence of D2 altered expression of gene clusters associated with lipid metabolism, including PPARα signaling. Using 3T3-L1 adipocytes, which express high levels of D2, we confirmed that knockdown of D2 modified genomic responses to fibrate treatment. We next evaluated the impact of D2 on effects of fibrates in a mouse model of diet-induced obesity. Fenofibrate treatment opposed the development of obesity, hypertriglyceridemia, and insulin resistance. However, these effects were unaffected by D2 genotype. We concluded that D2 can modulate genomic responses to fibrates, but that these effects are not sufficiently robust to alter the effects of fibrates on diet-induced obesity phenotypes.

Pharmacogenomics, lipid disorders, and treatment options

Statins form the backbone of lipid-lowering therapy in the prevention of cardiovascular disease. Numerous studies have evaluated the effect of genomics on the clinical efficacy and adverse effects of statins. Several gene variants that can be linked to either the pharmacokinetics or pharmacodynamics of statins have been identified as potentially important, although there are some discrepant findings among studies. Effect sizes are modest for lipid-lowering efficacy and perhaps somewhat larger for risk of myopathy, although results are inconsistent. Pharmacogenomics of nonstatin lipid-lowering agents have not been evaluated to the same extent, given their relatively limited use, although there are some promising candidate genes for further study. Finally, with several new classes of lipid-lowering therapies soon becoming available, there may be a potential application for pharmacogenomics to identify patients ideally suited to receive-or those who should avoid-specific medications.

The involvement of mitochondrial amidoxime reducing components 1 and 2 and mitochondrial cytochrome b5 in N-reductive metabolism in human cells

The mitochondrial amidoxime reducing component mARC is a recently discovered molybdenum enzyme in mammals. mARC is not active as a standalone protein, but together with the electron transport proteins NADH-cytochrome b5 reductase (CYB5R) and cytochrome b5 (CYB5), it catalyzes the reduction of N-hydroxylated compounds such as amidoximes. The mARC-containing enzyme system is therefore considered to be responsible for the activation of amidoxime prodrugs. All hitherto analyzed mammalian genomes code for two mARC genes (also referred to as MOSC1 and MOSC2), which share high sequence similarities. By RNAi experiments in two different human cell lines, we demonstrate for the first time that both mARC proteins are capable of reducing N-hydroxylated substrates in cell metabolism. The extent of involvement is highly dependent on the expression level of the particular mARC protein. Furthermore, the mitochondrial isoform of CYB5 (CYB5B) is clearly identified as an essential component of the mARC-containing N-reductase system in human cells. The participation of the microsomal isoform (CYB5A) in N-reduction could be excluded by siRNA-mediated down-regulation in HEK-293 cells and knock-out in mice. Using heme-free apo-CYB5, the contribution of mitochondrial CYB5 to N-reductive catalysis was proven to strictly depend on heme. Finally, we created recombinant CYB5B variants corresponding to four nonsynonymous single nucleotide polymorphisms (SNPs). Investigated mutations of the heme protein seemed to have no significant impact on N-reductive activity of the reconstituted enzyme system.